A Mixed-integer Multi-objective Maintenance and Production Workforce Planning Model

This study tackles the dilemma of producing a cooperative workforce planning involving maintenance and production departments. Its focus is on instituting workforce equilibrium between maintenance and production departments. This is necessary in order to ensure the optimal utilisation of manufacturing resources (time, equipment and funds). This maintenance-production problem was modelled using a mixed-integer multi-objective approach. The model minimises the workforce, rework and scrap, inventory holding cost and machine usage costs while maximising the average achieved machine availability. The model accounts for expected products’ demand, the amount of expected defective products, workforce size, rest period and finished good inventory. Due to the nonlinear relationships among the maintenance-production variables, a big bang-big crunch (BB-BC) algorithm and genetic algorithm (GA) were selected as solution methods for the model. The proposed model performance was validated in a household utensils manufacturing plant under the conditions of workers’ rest and without rest periods considerations. Based on the results obtained, the BB-BC algorithm performed better than the GA in terms of fitness function and computational time. The model performance with workers’ rest period consideration generated higher achieved machine availability value than when workers’ rest period was not considered. The optimised maintenance-production variables results confirmed the model’s capability to generate acceptable solutions for the case study. © 2017, Springer Nature Singapore Pte Ltd.